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Premature failure in lead-acid batteries used in starting, lighting, and ignition applications has led to warranty issues which can be resolved by predicting the contributing factors of battery aging and evaluating different design alternatives. Battery degradation in real vehicles is accelerated by dark currents from an integrated dashboard camera which are drawn while the ignition is turned off, high ambient temperatures, a shortage of the battery charge rate, and the intermittent occurrence of bad starts during idle-stop-and-go operation. Existing battery durability verification requires a long period of more than 4 months using experimental deep discharge testing and does not reflect the various actual vehicle driving conditions of the customer. In order to improve this, the present work aims to develop a battery aging prediction model that reflects the various operating conditions of actual vehicle driving patterns.

Integration of advanced battery systems into the next generation of hybrid and electric vehicles will require significant design, analysis, and test efforts. One major design issue is the thermal management of the battery pack. Analysis tools are being developed that can assist in the development of battery pack thermal design and system integration. However, the breadth of thermal design issues that must be addressed requires that there are a variety of analysis tools to address them efficiently and effectively. A set of battery modeling tools has been implemented in the thermal modeling software code PowerTHERM. These tools are coupled thermal-electric models of battery behavior during current charge and discharge. In this paper we describe the three models in terms of the physics they capture, and their input data requirements. We discuss where the capabilities and limitations of each model best align with the different issues needed to be addressed by analysis.

Commercial vehicle manufacturers are investing substantial resources into the development and testing of advanced battery systems for the next generation of hybrid and electric vehicles. Likewise the US army is investing in lithium ion battery research for power and energy applications including SLI (starter, lights, and ignition), silent watch, unmanned vehicles, and directed energy weapons. A major design constraint is the management of the heat generated by Li-Ion battery systems. Extreme battery temperatures impact both the performance and reliability of the battery system as well as the overall operation of the vehicle. Analysis tools that can address vehicle and battery thermal management issues are needed to accelerate this development. To meet that need, a coupled thermal-electric model for battery cells and packs has been developed and implemented into the existing thermal modeling software RadTherm.

The performance of lithium-ion batteries, in terms of capacity, safety, or life, is strongly dependent on operating temperature. Users and suppliers of Li-ion cells and packs must provide thermal management systems that keep the batteries operating within an acceptable temperature envelope to ensure reliable performance. The design of these systems depends on validated thermal-electrical models of battery behavior when subjected to various driving cycles and environmental conditions. A number of battery models have been developed for use in computer-aided engineering design studies, ranging in complexity from simple equivalent circuit models to multi-scale, multi-physics simulations of electro-chemical processes. One model that accomplishes a favorable compromise between simulation complexity and representative physics employs an empirical approach to capture discharge behavior as a function of current density and the depth-of-discharge (or charge depletion) on an electrode.